About the Journal
AI, Big Data and Quantitative Methods in Finance (ABQ) is a peer-reviewed scholarly journal that publishes high-quality research on the application of artificial intelligence, big data analytics, and quantitative methods in the field of finance. The journal serves as an interdisciplinary platform for academics, researchers, and practitioners to disseminate innovative theoretical and empirical studies that advance financial decision-making, risk management, financial markets analysis, and financial technology development.
ABQ welcomes original research articles, review papers, and methodological studies that explore machine learning, data science, econometrics, statistical modeling, optimization techniques, and computational finance applied to banking, investment, corporate finance, insurance, and financial markets. The journal emphasizes rigorous quantitative approaches and data-driven insights that contribute to both academic literature and practical financial solutions.
By integrating emerging digital technologies with advanced quantitative techniques, ABQ aims to foster knowledge exchange, encourage innovation, and support the development of sustainable, efficient, and resilient financial systems at both national and global levels.
Current Issue
Vol. 1 No. 1 (2026): ABQ Vol. 1 No. 1, April 2026
This issue consists of 5 articles from 19 authors affiliated with 6 institutions from 2 countries, including:
- Indonesia (Bank Indonesia, IPB University,PMI-International Business School, Universitas Bhayangkara Jakarta Raya, PT Gema Mulia Semesta (Souvia))
- Malaysia (Universiti Putra Malaysia)
Published:
2026-04-29
